Use Data Or Be Used By Data!

The August 26 issue of Seotistics is here for you!

How to deal with complexity? For example, what if you are working on a project with a lot of details and potential pitfalls?

We will go over some old concepts and develop some acumen.

What matters is being successful, remember that.

P.S. I've published a new article on Strategy, it's the best thing you will read this week!

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Data, Lots Of Data

One of the biggest scams of the last few years is "Big Data".

Everyone was preaching that data would grow exponentially and companies wouldn't have been able to manage it.

It didn't happen though.

Even in Digital Marketing, the data we have is always the same and many didn't even store the old data.

GA4 and GSC are omnipresent and without BigQuery (or a similar solution), you will lose all of your data (check this guide on the topic).

The key here is to only take what you need, for example:

You don't need all the country, device and page data (heck, not even query)
A lot of GA4 data you will never use
Semrush/Ahrefs data is fluff (excluding links)
Yes, GSC + GA4 + Crawl data are often what you need

I see many Google Sheets templates out there combining a lot of sources... you need half of that.

You don't need much data to make a valid decision.

In fact, as already stated multiple times, you need a good sample:

Framing The Problem

In many cases, it's all about deciding what to do.

Shall I optimize this or that page?

Do I want to make faster decisions?

Sitting down and thinking is the most underrated activity out there.

Whenever I consult, I always ask a lot of questions to frame the problem (if there is one).

This is what I mean, as detailed in my article about this Analytics Framework.

If you want to improve your website/company, you don't need to have a urgent problem.

I always recommend asking the following if you work with web data:

What existing processes are using data? How?
Do you have any data products working? e.g. dashboards
Which information would revolutionize your processes?

These are enough to frame the vast majority of problems.

If problems are recurring, you can build a table like this one:

From Complex To Simple

The goal of Analytics is to turn complex things into their essential components, simplified bits.

We get a lot of data, without any particular meaning at first, after some techniques, we extract insights.

Giving shape to chaos is the #1 skill of any Analyst:

Data per se doesn't hold any meaning, it's you who can do it.

Actually, it's not even like we extract insights from data, our understanding and knowledge detects patterns.

The final result should be simplified and hopefully, actionable.

Here is some stuff you can avoid:

Dashboards with Bounce Rate, Sessions, Users
Reporting on Avg. Position
Using complex ML models
AI for everything
The nth AI tool promising you the world

Complex solutions exist when the easiest ones don't work.

They are not supposed to replace the foundations anytime.

In most cases, your job will consist of handling easy tasks, even at a corporate level.

Companies often need the basics right and some good processes.

Methods & Techniques

You should always a method or a framework to handle projects.

That's it, this is how you both handle complexity and chaos!

I showed you this one for data analysis and content auditing:

Or this other one when evaluating solutions for your projects:

Auditing itself is a task that reduces complexity when done correctly.

Now it's trendy to devalue audits because they are not needed.

This is some bold and stupid take because you need to figure out what's going on first.

I've seen too many projects with duplicate content and initiatives because no one bothered to communicate and check what's on the website.

Making good decisions is another key component, like this picture summarizes:

How to Decide (Annie Duke) Visual Synopsis by Dani Saveker — Visual Synopsis | Tony robbins, Synopsis, The gift of imperfection — *Source:* https://www.pinterest.co.uk/pin/how-to-decide-annie-duke-visual-synopsis-by-dani-saveker-visual-synopsis--391813236337633087/

This is a summary of my favorite book on decision making.

If you want to learn even more about decision making, check my past issue.

Developing Acumen

Once you have some experience under your belt, you can start focusing on strategy and abstraction.

I am not a fan of doing only theory and zero practice because that makes you weak.

To deal with complex scenarios, you must work in those environments.

The acumen and sixth sense you'll develop can encompass:

understanding what NOT to do
recognizing fluff
spending less time on low-level activities

Acumen doesn't mean actively thinking about a solution or a proposal.

You can say it's your hunch, a sixth sense that tells you if something is bad or not.

This form of mastery is "passive", you don't have to explain to yourself how it works.
As usual, remember that you should be able to convert inputs into value.

Once you work on enough projects, you start understanding what moves the needle and what doesn't:

Some Projects Are Just Bad (My Experience)

Not every website can be saved. Maybe you are not a good fit or the idea itself is losing from the start.

You can easily spot them:

the scope is too wide or too narrow
the budget is insufficient
your gut tells you so (trust yourself)
they don't understand what you even do
the website/brand/products are mediocre

I've seen many like that and you can simply avoid them.

The #1 way to not to lose is to stop playing dangerous games.

Back then, I used to accept these projects because I lacked the acumen.

Now, I tend to refuse the majority of proposals because:

👉 the effort isn't worth it

👉 no direction/ambition

👉 doesn't fit my profile

In all the other cases, real value was added because:

✅ I asked a lot of questions and identified the (actual) problem

✅ I assessed the feasibility of some ideas

✅ I was realistic enough to avoid platitudes

This doesn't only apply to SEO but to any single problem I faced (mostly Consulting or Analytics).

When NOT To Use Data

There are cases too where data is pointless.

If you are dealing with a small website, 1st-party data doesn't matter.

Yes, you can do research and see what you can rank for or research your audience and competitors...

and yet, an expert in the industry will do much better than you.

Getting big with Discover/News requires knowledge about your industry, not just timely data.

You can have all the data in the world, it doesn't matter.

Domain knowledge is what makes the difference. Spend some time to know some specific industries, you won't regret it.

What You Can Do Now

The best practice is upskilling and testing new things.

In many SEO projects, you are requested to collaborate with developers/engineers.

While yes, you don't need to be a dev to tell them what to do, it's much more beneficial to have some skin in the game.

Chances are you'll get snobbed if you don't know what you are suggesting.

Or just be even smarter and focus on data, do it yourself!

My course can teach you how to apply Analytics for SEO:

[Analytics For SEO Course - v2]

If you want to be guided and start from scratch, this is the course for you!

This is the ultimate way of simplifying things.

You will:

✅ Use GSC and GA4 Data to their fullest potential

✅ Learn Python/SQL for your needs

✅ Get a complete blueprint for auditing websites

✅ Learn how to 10x your productivity

✅ Learn BigQuery to work on large websites

I teach you what's needed to go from 0 to a professional Data Analyst.

Even if you leave SEO, the foundations are the same for other jobs!

P.S. (Ab)use the referral system and get additional discounts 👀

Learn Analytics for SEO Now!

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